Latest edition·

The AI industry
in 5 minutes.

The stories, launches and research that actually matter. Reported fast, explained properly, with the noise cut.

Section

2 stories

Models

Frontier and open-weight model releases, benchmarks, pricing and what each one changes for the people who build on them.

Section

2 stories

Research

Papers, techniques and results from labs and universities, translated into what they mean in practice.

Section

2 stories

Tools

Developer tooling, agents, evaluation, gateways and the software stack around generative AI, tested and compared.

Section

2 stories

Industry

The economics, strategy and regulation of generative AI: who is spending, who is winning and why.

Comparisons & surveys Longer reads, built to be referenced

All comparisons →

ModelsExplainer

How to read a model card without getting fooled

Model cards are part specification, part marketing. Here is a field-by-field guide to the numbers that matter, the ones that are routinely gamed, and the questions a card should answer before you ship on it.

4 min read

ResearchExplainer

What "reasoning" models actually do differently

Reasoning models are trained to spend tokens thinking before they answer. Here is what that training involves, why it works on some problems and not others, and how to decide when to pay for it.

4 min read

More stories

Full archive →
  1. ResearchAnalysis

    Test-time compute changed the scaling roadmap. Here is what it costs

    For a decade, progress meant bigger training runs. Now labs can trade inference compute for capability instead. That shifts the economics from capex at the lab to opex at the user, and it changes what "a better model" means.

    3 min read

  2. ToolsComparison

    Five LLM gateways compared: routing, failover, governance and where each fits

    LLM gateways sit between your applications and model providers to handle routing, keys, failover, budgets and logging. We compare Bifrost, LiteLLM, Portkey, Kong AI Gateway and Cloudflare AI Gateway on the decisions that actually differ.

    4 min read

  3. ToolsSurvey

    The state of AI agent frameworks in 2026: a survey

    Agent frameworks have split into graph-based orchestrators, lab-native SDKs, multi-agent role systems and typed minimalists. This survey maps the landscape, the design bets behind each camp and the questions to ask before committing.

    4 min read

  4. IndustryEditorial

    Benchmarks became a marketing channel. Treat them like one

    Benchmark tables were meant to be measurements. They are now launch collateral, optimised for by every lab and reported under whatever settings look best. That does not make them useless, but it changes how they should be read.

    3 min read

  5. IndustryExplainer

    The real cost of running an AI product, line by line

    Token spend is the line everyone watches and rarely the largest. A working breakdown of where the money goes in a production generative AI product, from inference and evaluation to the humans in the loop.

    3 min read